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Record W4321360656 · doi:10.1353/ces.2022.0019

The Role of Financial Insecurity, Racial Discrimination, and Comorbid Health Conditions on Mental Health in Canada and the United States During the COVID-19 Pandemic

2022· article· en· W4321360656 on OpenAlexvenueaboutno aff
Jasmine Thomas, Murlat-Valérie Georges, Sally Ogoe, Avery Hallberg, Nikol Veisman, Lori Wilkinson, Paul Holley, Ravindra Shrestha, Kiera L. Ladner

Bibliographic record

VenueCanadian ethnic studies · 2022
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsRacismMental healthLogistic regressionDemographyEthnic groupGovernment (linguistics)Public healthPandemicPsychologyMedicinePolitical scienceCoronavirus disease 2019 (COVID-19)SociologyPsychiatryGender studiesDisease

Abstract

fetched live from OpenAlex

Canada and the United States have long histories of racism that permeate every institution and structure in our societies. While anti-racism movements have gained strength in recent years, we know very little about current rates of discrimination in the two countries or the impact on communities during the COVID-19 pandemic. Informed by critical race feminist theory, this paper examines levels of discrimination experienced by survey participants from Canada and the United States during the COVID-19 pandemic with a cross-sectional survey conducted during October 2021. We then assessed the broader impact of experiencing discrimination on depressive symptoms using logistic regression analysis. In both Canada and the US, multivariate logistic regression maintained that experiencing discrimination resulted in higher probabilities of reporting moderate to severe depressive symptoms. Other important factors included age, financial insecurity, and comorbid health conditions. Overall findings suggest that Indigenous, Black, and other racialized communities who experienced discrimination reported higher rates of depressive symptoms despite controlling for other factors. From a comparative perspective, discrimination rates were similar in Canada and the US, and had similar proportions across racial/ethnic groups. Discrimination rates did not vary significantly by gender, nor was gender a statistically significant risk factor for depressive symptoms. Further research, including qualitative studies, could fully assess the impact of gender on experiences of racism and depressive symptoms during the pandemic. The paper concludes with policy and public education suggestions to combat racial discrimination and highlights the need for added government action during times of crises. Résumé: Le Canada et les États-Unis ont une longue histoire de racisme qui se retrouve dans toutes les institutions et structures de nos sociétés. Bien que les mouvements antiracistes aient gagné en force ces dernières années, nous savons très peu de choses sur les taux actuels de discrimination dans les deux pays ou sur l’impact sur les communautés pendant la pandémie de COVID-19. S’inspirant de la théorie féministe du racisme critique, cet article examine les niveaux de discrimination subis par les participants du Canada and des États-Unis pendant la pandémie de COVID-19, à l’aide d’une enquête transversale menée en Octobre 2021. Nous avons ensuite évalué l’impact plus large de l’expérience de la discrimination sur les symptômes dépressifs en utilisant une analyse de régression logistique. Au Canada comme aux États-Unis, la régression logistique multivariée a confirmé que le fait d’avoir été victime de discrimination entraînait une probabilité plus élevée de signaler des symptômes dépressifs modérés ou graves. Les autres facteurs importants étaient l’âge, l’insécurité financière et la comorbidité. Les résultats globaux suggèrent que les communautés indigènes, noires et autres communautés racialisées ayant été victimes de discrimination présen-tent des taux plus élevés de symptômes dépressifs, malgré la prise en compte d’autres facteurs. D’un point de vue comparatif, les taux de discrimination étaient similaires au Canada et aux États-Unis, et présentaient des proportions similaires dans tous les groupes raciaux/ethniques. Les taux de discrimination ne varient pas de manière significative en fonction du sexe, et le sexe n’est pas un facteur de risque statistiquement significatif pour les symptômes dépressifs. D’autres recherches, notamment des études qualitatives, pourraient permettre d’évaluer pleinement l’impact du sexe sur les expériences de racisme et les symptômes dépressifs pendant la pandémie. L’article se termine par des suggestions de politiques et d’éducation du public pour lutter contre la discrimination raciale et souligne la nécessité d’une action gouvernementale supplémentaire en période de crise.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.607
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.111
GPT teacher head0.432
Teacher spread0.321 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2022
Admission routes2
Has abstractyes

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